In managed forests, there is an ongoing need to be able to inventory the types of trees that are growing in a given area. For example, in conifer forests, hardwood trees may be initially be viewed as an undesirable species that should be removed because they compete for water and nutrients with a desired species. However, if the hardwoods grow to such a size that they become harvestable, then the trees have their own value and should be inventoried.
As managed forests become increasingly large, it is becoming too costly to physically inventory all the areas of the forest. Therefore, remote sensing technology is becoming increasingly used to provide information about the types and ages of the trees that are in the forest. With remote sensing, aerial or satellite images of an area of interest in the forest are received that contain data for different spectral bands. From the remotely sensed images, the spectral data can be interpreted to provide information about the vegetation that is growing in the area of interest.
One commonly used measure of the spectral data is the Vegetation Index (VI). VI is most often calculated by dividing the near infrared spectral data received from a region of interest by the red light spectral data for the same region of interest. The Vegetation Index correlates with biomass growing in the area of interest. However, the conventional method of calculating VI is not very effective at differentiating between different types of vegetation in the area of interest.